Analyzing Relationships of Necessity Not Just<i>in Kind</i>But Also<i>in Degree</i>

Abstract

Analyzing relationships of necessity is important for both scholarly and applied research questions in the social sciences. An often-used technique for identifying such relationships-<i>fuzzy set Qualitative Comparative Analysis</i> (fsQCA)-has limited ability to make the most out of the data used. The set-theoretical technique fsQCA makes statements <i>in kind</i> (e.g., "a condition or configuration is necessary or not for an outcome"), thereby ignoring the variation <i>in degree</i>. We propose to apply a recently developed technique for identifying relationships of necessity that can make both statements <i>in kind</i> and <i>in degree</i>, thus making full use of variation in the data: <i>Necessary Condition Analysis</i> (NCA). With its ability to also make statements <i>in degree</i> ("a specific level of a condition is necessary or not for a specific level of the outcome"), NCA can complement the <i>in kind</i> analysis of necessity with fsQCA.